Those students who are interested in graduate research projects either in the form of Research Internship or Graduate Course ECE2500 may reach out through email to schedule a meeting. For particular openings, I may also post some separate advertisement.

• [Oct 2024] I have currently no new opening for ECE2500. I will be most likely offering new projects in Winter 2025. In case interested, please reach out by February 2025.

• [Oct 2024] I am teaching "ECE 1508: Applied Learning" and "ECE 1513: Introduction to Machine Learning" in Winter 2025.

• [Sep 2024] I am attending MLSP 2024, this year at Imperial College.

• [Sep 2024] I am teaching "ECE 1508: Applied Learning" in Fall Semester 2024.

• [May 2024] I am giving the course "ECE 1508 - Special Topics in Communications: Reinforcement Learning" in Summer Semester 2024.

• [April 2024] The page for the course "Applied Deep Learning" has been migrated permanently to this link. To watch the course videos you need to login with UTORid. The lecture-notes are however available publicly. 

• [January 2024] I am giving the course "ECE 1508 - Special Topics in Communications: Applied Deep Learning" in Winter Semester 2024.

• [January 2024] I am starting my new position as Assistant Professor - Teaching Stream in the Department of Electrical and Computer Engineering at the University of Toronto.

• [September 2023] My grant proposal entitled “Bayesian Learning and Model Fitting via Nonlinear Models” has won the German Research Foundation (DFG) Walter-Benjamin Postdoctoral Fellowship Award hosted by Princeton University.

• [June 2023] I am now on the Mathematics Genealogy Project. Check out my page here!

• [May 2023] My course "Information Theory and Coding" in Winter 2022-23 has been selected as the Best Lecture in the Faculty of Engineering at FAU.

• [Feb 2023] I am joining the Wireless Computing Lab (WCL) in the Department of Electrical and Computer Engineering at the University of Toronto.

• [Nov 2022] The book "Compressed Sensing in Information Processing" has been published. This book has been prepared throughout the last phase of the DFG-funded special session Compressed Sensing in Information Processing (CoSIP). Checkout our contribution in Chapter 5. In this chapter, we have given a comprehensive introduction to the replica method and its application to asymptotic analysis of Bayesian-type algorithms.

• [Jul 2022] I am giving an invited talk at the Random Matrices and Random Landscapes (RMRL 2022) conference in honor of Yan Fyodorov's 60th birthday. The talk is entitled "Bayesian Inference with Nonlinear Generative Models". The slides of my presentation can be found here.

• Machine Learning and Statistical Learning Theory
  Bayesian Inference, Machine Learning, Regression, Approximate Message Passing, Federated Learning

• Statistical Signal Processing
  Compressive Sensing, Detection Theory, Estimation Theory, Sensor Fusion

• Statistical Mechanics and Its Connection to Information Processing
  Replica Method, Information-theoretic Interpretation of Physical Models, Large Deviations Theory, Mean-field Theory, Random Matrix Theory

• Information Theory
  Network Information Theory, Information Theoretic Secrecy, Secret Key Agreement

• Computation and Communications
  Computation Coding, Distributed Coded Computing

• Wireless Communications
  Signal Processing for Communications

The lecture materials of my courses at FAU can still be accessed through StudOn. You can also download the lecture-notes here. The lecture-notes have been updated last time on Winter 2022-23. The version on GitHub is the final version, and hence could contain some changes compared to the older versions on the StudOn pages of previous semesters.